
Artificial Intelligence for Humans - AI explained easy





This book provides an accessible introduction to the world of Artificial Intelligence, exploring its principles and applications in everyday life. With no coding or math required, readers can gain a better understanding of AI and its implications.▼
Course Feature
Cost:
Free
Provider:
Udemy
Certificate:
No Information
Language:
English
Start Date:
Course Overview
❗The content presented here is sourced directly from Udemy platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [March 06th, 2023]
This course, Artificial Intelligence for Humans - AI explained easy, provides an overview of the fundamentals of Artificial Intelligence (AI). It covers topics such as machine learning, natural language processing, computer vision, face recognition, data science, and recommender systems. Students will gain an understanding of the basics of AI and how it can be used to solve real-world problems. They will also learn how to apply AI techniques to their own projects. By the end of the course, students will have a better understanding of AI and its potential applications.
[Applications]
After completing this course, students can apply their knowledge of Artificial Intelligence to a variety of tasks. They can use machine learning to create predictive models, natural language processing to build chatbots, computer vision to develop facial recognition systems, and data science to create recommender systems. Additionally, they can use their understanding of AI to develop new applications and technologies.
[Career Paths]
1. Artificial Intelligence Engineer: Artificial Intelligence Engineers are responsible for developing and deploying AI-based solutions to solve complex problems. They use a variety of techniques such as machine learning, natural language processing, computer vision, and face recognition to create AI-based systems. They also need to be able to analyze data and develop algorithms to improve the performance of AI-based systems. The demand for AI Engineers is growing rapidly as more companies are looking to leverage AI to improve their operations.
2. Data Scientist: Data Scientists are responsible for analyzing large datasets to uncover patterns and insights. They use a variety of techniques such as machine learning, natural language processing, and computer vision to uncover insights from data. They also need to be able to develop algorithms to improve the performance of AI-based systems. The demand for Data Scientists is growing rapidly as more companies are looking to leverage AI to improve their operations.
3. Machine Learning Engineer: Machine Learning Engineers are responsible for developing and deploying machine learning models to solve complex problems. They use a variety of techniques such as natural language processing, computer vision, and face recognition to create AI-based systems. They also need to be able to analyze data and develop algorithms to improve the performance of AI-based systems. The demand for Machine Learning Engineers is growing rapidly as more companies are looking to leverage AI to improve their operations.
4. Natural Language Processing Engineer: Natural Language Processing Engineers are responsible for developing and deploying natural language processing models to solve complex problems. They use a variety of techniques such as machine learning, computer vision, and face recognition to create AI-based systems. They also need to be able to analyze data and develop algorithms to improve the performance of AI-based systems. The demand for Natural Language Processing Engineers is growing rapidly as more companies are looking to leverage AI to improve their operations.
[Education Paths]
1. Bachelor of Science in Artificial Intelligence: This degree program focuses on the fundamentals of AI, including machine learning, natural language processing, computer vision, and data science. Students learn to develop algorithms and models to solve complex problems, as well as gain an understanding of the ethical implications of AI. This degree is becoming increasingly popular as AI technology advances and more businesses are looking to incorporate AI into their operations.
2. Master of Science in Data Science: This degree program focuses on the application of data science to solve real-world problems. Students learn to analyze large datasets, develop predictive models, and create visualizations to gain insights from data. This degree is becoming increasingly popular as businesses look to leverage data to gain a competitive edge.
3. Master of Science in Machine Learning: This degree program focuses on the development of algorithms and models to solve complex problems. Students learn to develop and implement machine learning algorithms, as well as gain an understanding of the ethical implications of AI. This degree is becoming increasingly popular as businesses look to leverage machine learning to gain a competitive edge.
4. Doctor of Philosophy in Artificial Intelligence: This degree program focuses on the development of advanced AI algorithms and models. Students learn to develop and implement AI algorithms, as well as gain an understanding of the ethical implications of AI. This degree is becoming increasingly popular as businesses look to leverage AI to gain a competitive edge.
Pros & Cons
-
Quick and simple introduction
-
Engaging and knowledgeable instructor
-
Enlightening on the future
-
Good quick intro
-
Simple and coherent.
-
Less use of graphical contents
-
Celebrity lecture.
Course Provider
